Training-related motor plasticity and the representation of skill

运动技能是我们与世界互动的重要组成部分，但我们关于大脑结构和功能如何支持运动技能获得的模型严重不足--几乎完全缺乏任何支持神经可塑性的生理机制的证据。大多数运动神经可塑性研究只使用一组参与者在短时间内(主要是在一天内或两天内)接受单一任务的培训，这使得很难确定与学习本身有关的过程，也很难得出关于自然学习的结论，这通常需要几天、几周或几个月的培训。此外，绝大多数成像研究只研究了一两个既不定量也不与大脑生理学有强烈联系的成像指标；这使得进行纵向比较变得困难，也不可能对可塑性的生理标志做出推断。如果没有一个更完整的模型来解释生理过程(如髓鞘形成、树突分枝和血管增殖)如何支持可塑性，我们的理解将局限于何时何地发生“变化”，没有迹象表明发生了什么变化。因此，我们必须开发一个更具生理学信息的框架，以生成更具体的人类神经可塑性时间过程的机制模型。我的总体研究目标是更深入地了解大脑如何通过神经可塑性过程支持运动技能的获得。这里描述的短期目标将通过以下方式开发一个人类运动神经可塑性的生理信息模型：确定大脑中支持序列特定可塑性本身的区域(除了操作的影响之外)，表征它们的变化的时间过程，并识别支持神经可塑性的假定的神经生理机制。这项拟议的工作基于一个独特而丰富的超高场(7T)多模式定量磁共振成像(MRI)数据集，该数据集之前是由我和Colloborers收集的。对两组受试者进行连续5天的精细运动控制视觉-运动序列学习任务(顺序夹紧力任务)训练，每组20人。每天采集多模式定量磁共振成像，包括对髓鞘、细胞密度、组织微结构、静息血流量、血容量和铁敏感的序列。这一独特的数据集将被HQP使用，包括2个博士和3个硕士，以开发与训练相关的结构、功能和多模式神经可塑性的生理信息模型，关键是利用我们对收集的多模式定量MRI指标的生理起源的知识来识别与训练相关的神经可塑性的机械时间过程。总而言之，这项拟议的研究是从机械论上理解我们的大脑如何学习运动技能的关键的第一步。

Motor skills are a crucial component of our interaction with the world, yet our models for how the structure and function of the brain support their acquisition are severely underspecified - almost completely lacking any evidence for the physiological mechanisms that support neuroplasticity. Most motor neuroplasticity studies use only a single group of participants trained on a single task over a short period of time (predominantly within a single day or across two), making it difficult to identify processes linked to learning per-se or draw conclusions about naturalistic learning that often requires days, weeks, or months of training. In addition, imaging studies overwhelmingly investigate only one or two imaging metrics that are neither quantitative nor strongly linked to brain physiology; making it both difficult to perform longitudinal comparisons and impossible to make inferences about the physiological markers of plasticity. Without a more complete model for how physiological processes (such as myelination, dendritic arborization, and vascular proliferation) support plasticity, our understanding will be limited to where and when "change" occurred, with no indication of what changed. Thus, we must develop a more physiologically-informed framework to generate more specific mechanistic models of the timecourse of human neuroplasticity. My overall research goal is to develop a deeper understanding of how the brain supports the acquisition of motor skills through the process of neuroplasticity. The short-term objectives porposed here will develop a physiologically-informed model of human motor neuroplasticity by: determining the regions of the brain that support sequence-specific plasticity per-se (over and above the effect of performance), characterizing their timecourses of change, and identifying the putative neurophysiological mechanisms that support neuroplasticity. The proposed work is based on a unique and rich Ultra-high field (7T) multimodal quantitative magnetic resonance imaging (MRI) dataset that was previously collected by myself and colloborators. Two groups of 20 participants (active, control) were trained on a visuo-motor sequence learning task of fine motor control (sequential pinch force task) over 5 consecutive days. Multimodal quantitative MRI was acquired on each day, and included sequences sensitive to myelin, cell density, tissue microstructure, resting blood flow, blood volume, and iron. This unique dataset will used by HQP including 2 PhDs and 3 Masters to develop a physiologically-informed model of structural, functional and multimodal training-related neuroplasticity, crucially leveraging our knowledge of the physiological origins of the collected multimodal quantitative MRI metrics to identify the mechanistic timecourse of training-related neuroplasticity. Together, the proposed research is a critical first step towards a mechanistic understanding of how our brains learn motor skills.